code: def read_csv(filename, loss_name="val/loss"):
      import codecs
      import csv
  
      fit_out = {}
      with codecs.open(filename, encoding="utf-8-sig") as f:
          for row in csv.DictReader(f, skipinitialspace=True):
              if row[loss_name]:
                  fit_out[row["epoch"]] = {"val_loss": row[loss_name]}
      return fit_out
  
imports: import torch
  import torch.nn
  import warnings
  import random
  import numpy
  from torch.utils.data import TensorDataset, DataLoader
  import numpy
  import multiprocessing
  import warnings
  import math
label_desc: Use image node_id 12 for calling a global function with example usage: read_csv(filename, loss_name) and returns: fit_out